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IEEE Transactions on Intelligent Vehicles is a peer-reviewed journal published by IEEE, covering Autonomous Vehicle Technology and Safety, Traffic control and management, Vehicle Dynamics and Control Systems. Over its lifetime it has published 2,425 papers, which have received 61,785 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Intelligent Vehicles, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Intelligent Vehicles style. No sign-up. |
| Abbreviation (ISO-4) | TIV |
| Publishes research in | Autonomous Vehicle Technology and Safety Traffic control and management Vehicle Dynamics and Control Systems Robotic Path Planning Algorithms Robotics and Sensor-Based Localization |
| ISSN | 2379-8858 |
| Citation impact (2-yr) | 8 |
| h-index | 103 |
| i10-index | 1,233 |
| Top institutions publishing here | Chinese Academy of Sciences |
| Journal website | ieeexplore.ieee.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation. Safety-critical tasks that must be executed by a self-driving vehicle include planning of motions through a dynamic environment shared with other vehicles and pedestrians, and their robust executions via feedback control. The…
In this paper, we propose a survey of the Simultaneous Localization And Mapping (SLAM) field when considering the recent evolution of autonomous driving. The growing interest regarding self-driving cars has given new directions to localization and mapping techniques. In this survey, we give an overview of the different branches of SLAM before going into the…
In order to drive safely in a dynamic environment, autonomous vehicles should be able to predict the future states of traffic participants nearby, especially surrounding vehicles, similar to the capability of predictive driving of human drivers. That is why researchers are devoted to the field of trajectory prediction and propose different methods. This paper is…
Intelligent vehicles (IVs) have gained worldwide attention due to their increased convenience, safety advantages, and potential commercial value. Despite predictions of commercial deployment by 2025, implementation remains limited to small-scale validation, with precise tracking controllers and motion planners being essential prerequisites for IVs. This article reviews state-of-the-art motion planning methods for IVs, including pipeline planning…
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks, lack of systematic summary and research directions in the future. Here we propose…
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